The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XXXVIII-3/W22
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-3/W22, 215–219, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-3-W22-215-2011
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-3/W22, 215–219, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-3-W22-215-2011

  26 Apr 2013

26 Apr 2013

MOTION COMPONENT SUPPORTED BOOSTED CLASSIFIER FOR CAR DETECTION IN AERIAL IMAGERY

S. Tuermer1, J. Leitloff1, P. Reinartz1, and U. Stilla2 S. Tuermer et al.
  • 1Remote Sensing Technology Institute, German Aerospace Center (DLR) Oberpfaffenhofen, Germany
  • 2Photogrammetry and Remote Sensing, Technische Universitaet Muenchen (TUM) Arcisstrasse 21, 80333 Munich, Germany

Keywords: Vehicle detection, AdaBoost, HoG features, Aerial image sequence, Motion mask

Abstract. Research of automatic vehicle detection in aerial images has been done with a lot of innovation and constantly rising success for years. However information was mostly taken from a single image only. Our aim is using the additional information which is offered by the temporal component, precisely the difference of the previous and the consecutive image. On closer viewing the moving objects are mainly vehicles and therefore we provide a method which is able to limit the search space of the detector to changed areas. The actual detector is generated of HoG features which are composed and linearly weighted by AdaBoost. Finally the method is tested on a motorway section including an exit and congested traffic near Munich, Germany.